Arpège(Action de Recherche Petite Echelle Grande Echelle) from Meteo France
4 times per day, from 08:00, 14:00, 20:00, and 00:00 UTC
Greenwich Mean Time:
12:00 UTC = 13:00 BST
0.1° x 0.1° (Europe)
0.5° x 0.5°
Sea Level Pressure in hPa
The surface chart (also known as surface synoptic chart) presents the distribution of
the atmospheric pressure observed at any given station on the earth's surface
reduced to sea level.
You can read the positions of the controlling weather features (highs, lows, ridges or
troughs) from the distribution of the isobars (lines of equal sea level pressure).
The isobars define the pressure field. The pressure field is the dominating player in
the weather system.
Additionally, this map helps you to identify synoptic-scale waves and gives you a first
estimate on meso-scale fronts.
ARPEGE uses a set of primitive equations with a triangular spectral truncation on the horizontal, with a variable horizontal resolution, with a finite elements representation on the vertical and a “sigma-pressure” hybrid vertical coordinate. It also utilizes a temporal two time level semi-implicit semi-lagrangian scheme. The horizontal resolution of the ARPEGE model is around 7.5km over France and 37km over the Antipodes. It has 105 vertical levels, with the first level at 10m above the surface and an upper level at around 70km. Its time step is of 360 seconds.
Numerical weather prediction uses current weather conditions as input into mathematical models of the atmosphere to predict the weather. Although the first efforts to accomplish this were done in the 1920s, it wasn't until the advent of the computer and computer simulation that it was feasible to do in real-time. Manipulating the huge datasets and performing the complex calculations necessary to do this on a resolution fine enough to make the results useful requires the use of some of the most powerful supercomputers in the world. A number of forecast models, both global and regional in scale, are run to help create forecasts for nations worldwide. Use of model ensemble forecasts helps to define the forecast uncertainty and extend weather forecasting farther into the future than would otherwise be possible.
Wikipedia, Numerical weather prediction, http://en.wikipedia.org/wiki/Numerical_weather_prediction
(as of Feb. 9, 2010, 20:50 UTC).